About
Highly accomplished Machine Learning Scientist and Engineer with 5+ years of experience spearheading the development and deployment of cutting-edge AI/ML and LLM solutions across diverse industries. Proven ability to drive significant business impact, optimize complex systems for scale and performance, and lead innovative research initiatives, resulting in up to 5% increases in watch duration, $20M quarterly revenue, and 50% improved cross-entropy in models.
Work
San Jose, CA, US
→
Summary
Leading advanced machine learning research and development to enhance core ranking models and retrieval systems, significantly improving user engagement metrics.
Highlights
Led scaling law and feature interaction research for a full-scale replacement of the main ranking model with a new SOTA model, collaborating with three senior researchers to achieve a 5% increase in Watch Live Duration (AWLD) org-wide.
Experimented with SOTA model architectures, including transformers and stacked networks, to improve scaling performance by 5x parameters and boost UAUC by 2%.
Spearheaded the redesign of the entire retrieval system, developing a novel generative retriever model that leverages Trinity clustering to learn explicit user interest, enhancing diversity metrics by +10% and AWLD by 1.4%.
Designed and implemented Transformer-based sequence modeling in the first-stage ranking model, improving UAUC by 0.6% and increasing watch duration by 1% through 100 user interactions.
Integrated a SOTA lifelong memory module to extend sequence modeling contextual range, resulting in a 2% improvement in watch duration.
Seattle, WA, US
→
Summary
Developed and scaled large-scale machine learning features and data pipelines to enhance user understanding and automate merchandiser actions for Amazon Device web pages.
Highlights
Developed a new LLM feature to improve user understanding on device detail pages by implementing a billion-scale embedding retrieval system, streamed via Kafka and Kubernetes, to achieve improved latency and serve 7M daily visits.
Developed and scaled large data pipelines with a scalable backend leveraging AWS S3 and API Gateway, automating merchandiser actions on Amazon Device web pages that reach over 360M customers annually.
Generated $20M quarterly revenue by automating merchandiser actions on Amazon Device web pages, directly contributing to business growth and efficiency.
Los Angeles, CA, US
→
Summary
Led the development and deployment of a multi-agent LLM framework and established strategic research partnerships to advance AI capabilities.
Highlights
Developed and deployed the first-ever multi-agent LLM framework and application in Tensorflow, enabling LLM agent cooperation and improving cross-entropy by 50% through agent fine-tuning with QLoRA.
Led a research partnership with Google, applying directed-cyclic graph simulations for medical information alignment to advance SOTA LLM capabilities.
Charlottesville, VA, US
→
Summary
Conducted advanced research in machine learning, focusing on text generation fairness and personalized explanations, contributing to a conference paper and outperforming baseline models.
Highlights
Contributed to a conference paper on text generation fairness models, aligning experiments tracking with training parameters to ensure robust and unbiased AI outcomes.
Trained and fine-tuned a PETER transformer with Pytorch, leveraging distributed GPUs and multi-task learning to provide personalized explanations on terabytes of review data.
Outperformed the GPT-3 baseline in accuracy (BLEU) and text quality for personalized explanations, demonstrating superior model performance and efficiency.
New York, NY, US
→
Summary
Co-founded and scaled an ML platform to optimize company meetings through employee feedback, leading product development and client acquisition.
Highlights
Co-founded BOUND, an ML platform recognized as a "Top 30" solution, securing initial funding to optimize company meetings with employee feedback.
Led product development with a 4-person engineering team, overseeing the entire lifecycle from concept to deployment.
Grew the platform to serve 35 B2B clients, demonstrating strong market penetration and business development capabilities.
Education
→
Bachelor of Arts
Computer Science
Grade: 3.8/4.0
Courses
Organizations: Organizer of HooHacks - Virginia's largest hackathon, SWE Consultant of Google Student Developer Club
Talks and Awards: TEDx Speaker at TEDxLynbrook - How Changing Society Changes Us | Single Sprout Speaker Series 2021 - Serverless: The Future of Software Architecture | UVA HooHacks Speaker - Frontend Design with CSS
Skills
Deep Learning
Pytorch, Tensorflow, Keras, LLM Pre and Post Training, Transformer, NLP, Feature Engineering, Recommendations.
Model Training and Optimization
Weights & Biases, Hyperparameter Tuning, Quantization, Distributed Training.
MLOps
AWS, Google Cloud, Kubernetes, Serverless Architectures, Kafka, Data Pipelining (Spark, Apache), Docker, CI/CD.